Artificial intelligence is making US midterm election experiences worse, according to security technologist Bruce Schneier and data scientist Nathan E Sanders. Voters have anxiety about AI's impacts, politicos use AI deepfakes to spread lies, and the White House is posting slopaganda. Meanwhile, candidates are missing an opportunity to use AI to make campaigning better.
Current AI use is not different from old web ads
The problem with American campaigns' current use of AI is that it's not very different from the web ads of 30 years ago, or television ads before that: they are all about inundating voters with the candidate's message. This one-to-many broadcasting is an uninspiring way to campaign, but not the only way. AI can help candidates connect one-to-one with as many people as possible, or facilitate many-to-many connections, engaging voters in deliberation about issues at scale.
One of the most promising applications of AI being developed by pro-democracy innovators around the world is broad listening. These tools can collect public input in a format much richer than checkboxes on a survey form.
Examples from Japan and Scotland
The newly founded Japanese political party Team Mirai has built a foundation for eliciting public input from voters at scale, in depth, and across the breadth of legislative policy issues. It has developed an AI interviewer to cultivate constituent input on policy. Through extended conversations with this chatbot, voters explore and share their perspectives on specific policy issues. The party has scaled this across a wide array of policy issues by integrating this functionality with an AI-powered portal for exploring bills.
Team Mirai describes itself as a "utility party", developing tools for any Japanese political party to use to connect with voters. So far, Japanese voters have exchanged more than 300,000 messages across 16,000 AI interviews. Team Mirai grew adoption by providing a real incentive to engage: that talking to their AI interviewer does more than just posting on a platform such as Twitter/X or, equivalently, shouting into a void. Users see evidence that the party is actually listening and might take action on their behalf.
Team Mirai party members have directly cited AI interviews from constituents during legislative committee hearings, published a synthesis of that input back for voters, and even amended their policy platform based on user input. The party has rapidly risen to win 12 seats in the Diet, and is explicitly following in the footsteps of the civic hackers in Taiwan's "gov zero" movement, who won political influence in their fight for transparency.
Other civic technologists and US tools
Other civic technologists are developing AI tools for scaling many-to-many conversations. CrownShy, a non-profit funded in part by the Scottish government, is building a platform to bring the Platonic ideal of the town hall debate into the digital age. Their Comhairle tool integrates AI interviewing tools with software for synthesizing diverse viewpoints, holding virtual assemblies, and sharing video testimonials to help legislatures – or campaigners – organize digital consultations of their constituents en masse.
One thing the AI-powered software of Team Mirai and CrownShy have in common is that they are open-source, meant for anyone to use. Even though they are projects funded by political parties – the upstart party in Japan and the ruling party in Scotland – they are built to make democratic processes better, not necessarily for partisan political advantage.
For interested candidates, there is a wealth of tools available, many of them US-grown. The Stanford-affiliated deliberation.io uses AI to facilitate structured dialogues among thousands of participants and has been piloted for public listening sessions by the city of Washington DC. The MIT-affiliated Cortico project provides tools that surface under-heard community perspectives from recorded conversations, and is now organizing listening sessions at libraries across the country. The US non-profit-built Talk to the City uses AI to analyze large datasets of stakeholder input. The US startup Remesh has a commercial offering that uses AI to generate recommendations from dialogue, which has been tested in policy development scenarios.
Tradition of civic technology and a signal of adoption
There is a long and proud tradition of this sort of "civic technology" in the United States. Two decades ago, the spirit of innovation to develop software for better politics and civic engagement was so strong in organizations like Code for America and the Obama 2008 campaign that Congress funded a new executive agency to bring these ideas to government: the US Digital Service. (The Trump administration repurposed the USDS to become the US Doge Service in 2025.)
One signal that candidates and political parties may start adopting these kinds of tools came this spring from Higher Ground Labs. The Democratic-aligned campaign tech investment firm launched a new fund targeting, in part, "AI-Native Campaign Systems" and "community-Led Messaging Platforms that surface authentic, bottom-up insights from real conversations".
AI is a multifaceted issue that deserves to be on the table in the midterms. So far, the powerful force of polarization in US politics seems to be separating the parties into the AI skeptics versus the AI boosters. Schneier and Sanders urge both voters and politicians to separate the technology of AI from its profiteers. They want big tech money out of politics, holding the AI companies accountable for the harm their models cause, taxing their revenues, and maybe even nationalizing them if the AI bubble bursts.
But they also think congressional candidates in the US midterms seeking authentic connection with voters, and seeking to differentiate themselves from their opponents, should be looking to use AI responsibly in their campaigning. The broad listening and deliberation tools pioneered by others around the world could make US politics more transparent, responsive and community-driven. The impact of AI on campaigning doesn't have to be all bad.
